The success of CRM Implementations? The failure of CRM strategies?

The success of CRM Implementations? The failure of CRM strategies?

CRM, as many have noted, is moving on. The first flush of excitement is passing, and most organisations are seriously into implementation and trying to deliver the benefits of their CRM systems.

In many cases, the reality doesn't seem to be living up to the promise. Most organisations claim to be adopting CRM so as to improve the quality of their relationships with their customers in order, of course, to improve profitability. Speak to many customers, and their view is different. Their disillusionment with poor quality service and communication through call centers and the web is growing.

Why this disillusionment? Many reasons and we intend to cover them in detail in the coming weeks. They include:
- Misunderstanding of the fundamental changes CRM introduces
- A focus on reducing customer contact costs, rather than improving contact value
- A lack of focus on understanding the customer
- Poor process design in call centers and web-sites
- Inability to manage the organisational change required to focus on customer

Despite these issues, we're encouraged to see that the promise of CRM is being met by those organisations that have the ability to drive through the necessary change. Such companies re-emphasise that a fundamental shift in how companies do business with their customers is under-way. They sometimes become victims of their own success. In the UK this week, IKEA, the Swedish-origin, retail furniture store, which has a fascinating, customer-focused business model, admitted that customers were finding the queues in its stores unacceptably long. It is trying to solve the problem by opening more stores, and keeping existing stores open long. The problems of success!! IKEA make a fascinating case study for CRM, outside the norm. More on IKEA later.

CRM systems are made up of a number of core components, which can be summarised as:
- Customer Knowledge:
- Customer Profitability, Trend Analyses
- Data Mining (segmentation, profiling,...

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